Biblio

Although function model has been widely applied to develop various operator decision support systems, the modeling process is essentially a manual work, which takes significant efforts on knowledge acquisition. It would greatly improve the efficiency of modeling if relevant information can be automatically retrieved from engineering documents. This paper investigates the possibility of automated transformation from P&IDs to a function model called MFM via AutomationML. Semantics and modeling patterns of MFM are established in AutomationML, which can be utilized to convert plant topology models into MFM models. The proposed approach is demonstrated with a small use case. Further topics for extending the study are also discussed.

Stealing confidential information from a database has become a severe vulnerability issue for web applications. The attacks can be prevented by defining a whitelist of SQL queries issued by web applications and detecting queries not in list. For large-scale web applications, automated generation of the whitelist is conducted because manually defining numerous query patterns is impractical for developers. Conventional methods for automated generation are unable to detect attacks immediately because of the long time required for collecting legitimate queries. Moreover, they require application-specific implementations that reduce the versatility of the methods. As described herein, we propose a method to generate a whitelist automatically using queries issued during web application tests. Our proposed method uses the queries generated during application tests. It is independent of specific applications, which yields improved timeliness against attacks and versatility for multiple applications.